COVID-19 VACCINATION ANALYSIS


Table of Contents:

About the Data:

This Notebook would not have been possible without this Dataset provided by @Gabriel Preda.

The Data contains the following information:

Importing Libraries:

We initialize the Python packages we will use for data ingestion, preparation and visualization. We will use :

Reading the Data:

Cleaning the Data:

As you can see, a lot of null values are present in the data. This may be because:

  1. The vaccination drive has just started and will take some time for all the countries to catch up.
  2. This Data is collected daily from Our World in Data GitHub repository for Covid-19, and thus during the creation of this dataset some in consistencies may have crept in.

There may be other reasons but let's move forward with cleaning the data and filling the missing values.

Other Apparent Inconsistencies

Exploratory Data Analysis:

Basic Info about Dataset

Amount of Vaccinated People

From the plot, some interesting facts stand out:

Country wise Daily Vaccination

From the plot, we can deduce:

Percent of Population Vaccinated

People vaccinated once VS People vaccinated twice

The above plot shows the World-Wide comparison between the First and Second Dose of the Vaccine

From the plot we can determine:

Market share of Vaccine Schemes

From the above charts, we can see that :

TreeMap of Total Vaccinations per country, grouped by Vaccine Scheme

Visualising on a Map

Animating the Vaccination Progress

Conclusion:

From our analysis we can conclude the following:

With this information we can realise that the Covid-19 vaccination drive is going at an incredible pace. Diseases like Polio and Smallpox, which caused many deaths, took decades and centuries to eradicate. At the current pace, Covid-19 can be eradicated in a period of 2 years.